X-Ray Tomographic Inspection Systems for the Identification of Specific Target Items

ABSTRACT

The present specification discloses an X-ray scanning system with a non-rotating X-ray scanner that generates scanning data defining a tomographic X-ray image of the object and a processor executing programmatic instructions where the executing processor analyzes the scanning data to extract at least one parameter of the tomographic X-ray image and where the processor is configured to determine if the object comprises a liquid, sharp object, narcotic, currency, nuclear materials, cigarettes or fire-arms.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 12/787,930, filed on May 26, 2010, which relies on U.S. PatentProvisional Application No. 61/181,068 filed on May 26, 2009, forpriority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/485,897,filed on Jun. 16, 2009, which is a continuation of U.S. patentapplication Ser. No. 10/554,656, filed on Oct. 25, 2005, and now issuedU.S. Pat. No. 7,564,939, which is a 371 national stage application ofPCT/GB04/01729, filed on Apr. 23, 2004 and which, in turn, relies onGreat Britain Application No. 0309387.9, filed on Apr. 25, 2003, forpriority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/371,853,filed on Feb. 16, 2009, which is a continuation of U.S. patentapplication Ser. No. 10/554,975, filed on Oct. 25, 2005, and now issuedU.S. Pat. No. 7,512,215, which is a 371 national stage application ofPCT/GB2004/01741, filed on Apr. 23, 2004 and which, in turn, relies onGreat Britain Application Number 0309383.8, filed on Apr. 25, 2003, forpriority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/651,479,filed on Jan. 3, 2010, which is a continuation of U.S. patentapplication Ser. No. 10/554,654, filed on Oct. 25, 2005, and now issuedU.S. Pat. No. 7,664,230, which is a 371 national stage application ofPCT/GB2004/001731, filed on Apr. 23, 2004 and which, in turn, relies onGreat Britain Patent Application Number 0309371.3, filed on Apr. 25,2003, for priority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/364,067,filed on Feb. 2, 2009, which is a continuation of U.S. patentapplication Ser. No. 12/033,035, filed on Feb. 19, 2008, and now issuedU.S. Pat. No. 7,505,563, which is a continuation of U.S. patentapplication Ser. No. 10/554,569, filed on Oct. 25, 2005, and now issuedU.S. Pat. No. 7,349,525, which is a 371 national stage filing ofPCT/GB04/001732, filed on Apr. 23, 2004 and which, in turn, relies onGreat Britain Patent Application Number 0309374.7, filed on April 25,2003, for priority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/758,764,filed on Apr. 12, 2010, which is a continuation of U.S. patentapplication Ser. No. 12/211,219, filed on Sep. 16, 2008, and now issuedU.S. Pat. No. 7,724,868, which is a continuation of U.S. Pat. No.10/554,655, filed on Oct. 25, 2005, and now issued U.S. Pat. No.7,440,543, which is a 371 national stage application ofPCT/GB2004/001751, filed on Apr. 23, 2004, and which, in turn, relies onGreat Britain Patent Application Number 0309385.3, filed on Apr. 25,2003, for priority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/697,073,filed on Jan. 29, 2010, which is a continuation of U.S. patentapplication Ser. No. 10/554,570, filed on Oct. 25, 2005, and now issuedU.S. Pat. No. 7,684,538, which is a 371 national stage application ofPCT/GB2004/001747, filed on Apr. 23, 2004, and which, in turn, relies onGreat Britain Patent Application Number 0309379.6, filed on Apr. 25,2003, for priority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/097,422,filed on Jun. 13, 2008, and U.S. patent application Ser. No. 12/142,005,filed on Jun. 19, 2008, both of which are 371 national stageapplications of PCT/GB2006/004684, filed on Dec. 15, 2006, which, inturn, relies on Great Britain Patent Application Number 0525593.0, filedon Dec. 16, 2005, for priority.

U.S. patent application Ser. No. 12/787,930 is also acontinuation-in-part of U.S. patent application Ser. No. 12/478,757,filed on Jun. 4, 2009, which is a continuation of U.S. patentapplication Ser. No. 12/364,067, filed on Feb. 2, 2009, which is acontinuation of U.S. patent application Ser. No. 12/033,035, filed onFeb. 19, 2008, and now issued U.S. Pat. No. 7,505,563, which is acontinuation of U.S. patent application Ser. No. 10/554,569, filed onOct. 25, 2005, and now issued U.S. Pat. No. 7,349,525, which is a 371national stage filing of PCT/GB04/001732, filed on Apr. 23, 2004 andwhich, in turn, relies on Great Britain Patent Application Number0309374.7, filed on Apr. 25, 2003, for priority. In addition, U.S.Patent Application number relies on Great Britain Patent ApplicationNumber 0812864.7, filed on Jul. 15, 2008, for priority.

U.S. patent application Ser. No. 12/787,930 is also a continuation-inpart of U.S. patent application Ser. No. 12/712,476, filed on Feb. 25,2010, which relies on U.S. Provisional Patent Application No. 61/155,572filed on Feb. 26, 2009 and Great Britain Patent Application No.0903198.0 filed on Feb. 25, 2009, for priority.

Each of the aforementioned PCT, foreign, and U.S. applications, and anyapplications related thereto, is herein incorporated by reference intheir entirety.

FIELD

The present application relates to X-ray scanning and, particularly tothe security screening of baggage, packages and other suspiciousobjects, such as sharp objects, knives, nuclear materials, tobacco,currency, narcotics, and liquids.

BACKGROUND

X-ray computed tomography (CT) scanners have been used in securityscreening in airports for several years. A conventional system comprisesan X-ray tube that is rotated about an axis with an arcuate X-raydetector that is rotated at the same speed around the same axis. Theconveyor belt on which the baggage is carried is placed within asuitable aperture around the central axis of rotation, and moved alongthe axis as the tube is rotated. A fan-beam of X-radiation passes fromthe source through the object to be inspected to the X-ray detectorarray.

The X-ray detector array records the intensity of X-rays passed throughthe object to be inspected at several locations along its length. Oneset of projection data is recorded at each of a number of source angles.From these recorded X-ray intensities, it is possible to form atomographic (cross-sectional) image, typically by means of a filteredback projection algorithm. In order to produce an accurate tomographicimage of an object, such as a bag or package, it can be shown that thereis a requirement that the X-ray source pass through every plane throughthe object. In the arrangement described above, this is achieved by therotational scanning of the X-ray source, and the longitudinal motion ofthe conveyor on which the object is carried.

In this type of system the rate at which X-ray tomographic scans can becollected is dependent on the speed of rotation of the gantry that holdsthe X-ray source and detector array. In a modern CT gantry, the entiretube-detector assembly and gantry will complete two to four revolutionsper second. This allows up to four or eight tomographic scans to becollected per second respectively.

As the state-of-the-art has developed, the single ring of X-raydetectors has been replaced by multiple rings of detectors. This allowsmany slices (typically 8) to be scanned simultaneously and reconstructedusing filtered back projection methods adapted from the single scanmachines. With a continuous movement of the conveyor through the imagingsystem, the source describes a helical scanning motion about the object.This allows a more sophisticated cone-beam image reconstruction methodto be applied that can in principle offer a more accurate volume imagereconstruction.

In a further development, swept electron beam scanners have beendemonstrated in medical applications whereby the mechanical scanningmotion of the X-ray source and detectors is eliminated, being replacedby a continuous ring (or rings) of X-ray detectors that surround theobject under inspection with a moving X-ray source being generated as aresult of sweeping an electron beam around an arcuate anode. This allowsimages to be obtained more rapidly than in conventional scanners.However, because the electron source lies on the axis of rotation, suchswept beam scanners are not compatible with conveyor systems whichthemselves pass close, and parallel, to the axis of rotation.

There is still a need for methods and systems that enable the rapidgeneration of tomographic images that have the capability of detectingcertain items of interest, including liquids, narcotics, currency,tobacco, nuclear materials, sharp objects, and fire-arms.

SUMMARY OF THE INVENTION

The present invention provides an X-ray scanning system for inspectingitems, the system comprising an X-ray source extending around a scanningvolume, and defining a plurality of source points from which X-rays canbe directed through the scanning volume, an X-ray detector array alsoextending around the scanning volume and arranged to detect X-rays fromthe source points which have passed through the scanning volume andproduce output signals dependent on the detected X-rays, and a conveyorarranged to convey the items through the scanning volume.

The present invention further provides a networked inspection systemcomprising an X-ray scanning system, a workstation and connection meansarranged to connect the scanning system to the workstation, the scanningsystem comprising an X-ray source extending around a scanning volume,and defining a plurality of source points from which X-rays can bedirected through the scanning volume, an X-ray detector array alsoextending around the scanning volume and arranged to detect X-rays fromthe source points which have passed through the scanning volume andproduce output signals dependent on the detected X-rays, and a conveyorarranged to convey the items through the scanning volume.

The present invention further provides a sorting system for sortingitems, the system comprising a tomographic scanner arranged to scan aplurality of scanning regions of each item thereby to produce a scanneroutput, analyzing means arranged to analyze the scanner output andallocate each item to one of a plurality of categories at least partlyon the basis of the scanner output, and sorting means arranged to sortitems at least partly on the basis of the categories to which they havebeen allocated.

The present invention further provides an X-ray scanning systemcomprising an X-ray source arranged to generate X-rays from a pluralityof X-ray source positions around a scanning region, a first set ofdetectors arranged to detect X-rays transmitted through the scanningregion, a second set of detectors arranged to detect X-rays scatteredwithin the scanning region, and processing means arranged to processoutputs from the first set of detectors to generate image data whichdefines an image of the scanning region, to analyze the image data toidentify an object within the image, and to process the outputs from thesecond set of detectors to generate scattering data, and to associateparts of the scattering data with the object.

The present invention further provides a data collecting system forcollecting data from an X-ray scanner, the system comprising a memoryhaving a plurality of areas each being associated with a respective areaof an image, data input means arranged to receive input data from aplurality of X-ray detectors in a predetermined sequence, processingmeans arranged to generate from the input data X-ray transmission dataand X-ray scattering data associated with each of the areas of theimage, and to store the X-ray transmission data and the X-ray scatteringdata in the appropriate memory areas.

The present invention further provides an X-ray scanning systemcomprising a scanner arranged to scan an object to generate scanningdata defining a tomographic X-ray image of the object, and processingmeans arranged to analyze the scanning data to extract at least oneparameter of the image data and to allocate the object to one of aplurality of categories on the basis of the at least one parameter.

In an embodiment, the present invention provides an X-ray scanningsystem comprising a scanner arranged to scan an object to generatescanning data defining a tomographic X-ray image of the object, andprocessing means arranged to analyse the scanning data to extract atleast one parameter of the image data and to allocate the object to oneof a plurality of categories on the basis of the at least one parameter.The processing means comprise: one or more parameter extractors foridentifying one or more predefined features in the tomographic X-rayimage, the identified features being low level parameters of the X-rayimage; each parameter extractor being arranged to perform a differentprocessing operation to determine a different parameter; one or moredecision trees for constructing high level parameters by analyzing theidentified low level parameters of the X-ray image; and a databasesearcher for mapping the X-ray image of the object as one of‘threat-causing’ or ‘clear’ by using the constructed high levelparameters of the X-ray image and predefined data stored in a databasecoupled with the database searcher. The parameter extractors aredesigned to operate on one of 2-dimensional images, 3-dimensional imagesand sinogram image data.

In another embodiment, the present invention provides a method fordetecting a predefined material by using an X-ray scanning systemcomprising a scanner arranged to scan an object to generate atomographic X-ray image of the object, and processing means arranged toanalyse the scanning data to extract at least one parameter of the imagedata and to allocate the object to one of a plurality of categories onthe basis of the at least one parameter. The method comprises the stepsof: configuring a plurality of parameter extractors for identifying oneor more predefined features in the tomographic X-ray image, theidentified features being low level parameters of the X-ray image;configuring one or more decision trees for constructing high levelparameters by analyzing the identified low level parameters of the X-rayimage; identifying the object as the predefined material by mapping theconstructed high level parameters of the X-ray image with stored datadefining the material. The method further comprises the step ofclassifying the X-ray image of the object as one of ‘threat-causing’ or‘clear’ by mapping the constructed high level parameters of the

X-ray image with predefined stored data.

In an embodiment, the present invention provides a method for detectinga liquid wherein the steps of configuring a plurality of parameterextractors for identifying one or more predefined features in thetomographic X-ray image and configuring one or more decision trees forconstructing high level parameters by analyzing the identified low levelparameters of the X-ray image comprise the steps of: configuring a firstparameter extractor to process the X-ray image to identify: the objectbeing scanned; an outer envelope defining the object being scanned, andone or more flat surfaces within an outer envelope of the object beingscanned; configuring a second parameter extractor to locate a contiguousvolume of a material of uniform density extending from each identifiedflat surface in a vertical direction;

and configuring a decision tree for: calculating the volume of thecontiguous volume of material located; assigning the calculated volumeto at least one predetermined shape corresponding to one of an ovalbottle, a rectangular bottle and a triangular bottle; calculating a meanreconstructed density of the contiguous volume; and transferring theparameters corresponding to volume, shape and density for identificationof the liquid by mapping against a database.

In another embodiment, the present invention provides a method fordetecting a narcotic wherein, the steps of configuring a plurality ofparameter extractors for identifying one or more predefined features inthe tomographic X-ray image and configuring one or more decision treesfor constructing high level parameters by analyzing the identified lowlevel parameters of the X-ray image comprise the steps of: configuring afirst parameter extractor to process the X-ray image to identifycontiguous volumes of low density material in at least sheet and bulkshapes; configuring a second parameter extractor to processes theidentified contiguous volumes to determine statistical properties of thecontiguous volumes; configuring a third parameter extractor foridentifying one or more collections of randomly oriented parts of smallvolume; and configuring a decision tree for correlating the parameterscorresponding to volume shape and statistical properties identified by aplurality of parameter extractors; and transferring the correlated datafor identification of the narcotic material by mapping against adatabase.

In yet another embodiment, the present invention provides a method fordetecting a currency wherein, the steps of configuring a plurality ofparameter extractors for identifying one or more predefined features inthe tomographic X-ray image and configuring one or more decision treesfor constructing high level parameters by analyzing the identified lowlevel parameters of the X-ray image comprise the steps of: configuring afirst parameter extractor to identify one or more “bow-tie” shapedfeatures in the X-ray image; configuring a second parameter extractor toidentify one or more rectangular shapes in multiples of predefinedphysical dimension of predefined denominations of currency; configuringa third parameter extractor for identifying repeating patterns in theparameters identified by the first and the second parameter extractors;configuring a fourth parameter extractor for generating statisticalproperties of the patterns identified by the first, the second and thethird parameter extractors; and configuring a decision tree forcorrelating the parameters identified by a plurality of parameterextractors; and transferring the correlated data for identification ofthe currency by mapping against a database.

In yet another embodiment, the present invention provides a method fordetecting cigarettes wherein, the steps of configuring a plurality ofparameter extractors for identifying one or more predefined features inthe tomographic X-ray image and configuring one or more decision treesfor constructing high level parameters by analyzing the identified lowlevel parameters of the X-ray image comprise the steps of: configuring afirst parameter extractor to identify repeating array structures with alength and width dimension consistent with predefined dimensions ofcigarettes; configuring a second parameter extractor to identifyrectangular volumes of predefined aspect ratio matching that ofpredefined cigarette packaging with a density that is consistent withpredefined brands of cigarettes; and configuring a decision tree forcorrelating the parameters identified by a plurality of parameterextractors; and transferring the correlated data for identification ofthe cigarettes by mapping against a database.

In yet another embodiment, the present invention provides a method fordetecting a special nuclear material or a shielded radioactive sourcewherein, the steps of configuring a plurality of parameter extractorsfor identifying one or more predefined features in the tomographic X-rayimage and configuring one or more decision trees for constructing highlevel parameters by analyzing the identified low level parameters of theX-ray image comprise the steps of: configuring a first parameterextractor to identify highly attenuating regions in the X-ray imagewhere the reconstructed pixel intensity is above a predefined thresholdvalue; and configuring a decision tree for: determining whether theattenuating region is part of a larger structure; evaluating at least ashape, a location and a size of the attenuating region if it isdetermined that the attenuating region is not a part of a largerstructure; and transferring the evaluated parameters corresponding tothe attenuating region for identification of the special nuclearmaterial or a shielded radioactive source by mapping against a database.

In yet another embodiment, the present invention provides a method fordetecting a pointed object or a knife wherein, the steps of configuringa plurality of parameter extractors for identifying one or morepredefined features in the tomographic X-ray image and configuring oneor more decision trees for constructing high level parameters byanalyzing the identified low level parameters of the X-ray imagecomprise the steps of: configuring a first parameter extractor to detectone or more protruding points in the X-ray image; configuring a secondparameter extractor to identify one or more blades having a predefinedlength to width aspect ratio; configuring a third parameter extractorfor identifying folded blades having a repeating structure of at leasttwo air gaps and three material fills; and configuring a decision treefor correlating the parameters identified by a plurality of parameterextractors; and transferring the correlated data for identification ofthe pointed object or knife by mapping against a database.

In yet another embodiment, the present invention provides a method fordetecting a fire arm wherein, the steps of configuring a plurality ofparameter extractors for identifying one or more predefined features inthe tomographic X-ray image and configuring one or more decision treesfor constructing high level parameters by analyzing the identified lowlevel parameters of the X-ray image comprise the steps of: configuring afirst parameter extractor to identify one or more cylindrical metaltubes in the X-ray image; configuring a second parameter extractor toidentify one or more trigger mechanism and firing pin; configuring athird parameter extractor for identifying high density slugs and bulletswith composition ranging from aluminium (density 2.7 g/cm3) to lead(density >11 g/cm3); and configuring a decision tree for correlating theparameters identified by a plurality of parameter extractors andassociated data; and transferring the correlated data for identificationof the currency by mapping against a database.

In another embodiment, the present invention is an X-ray scanning systemcomprising: a non-rotating X-ray scanner that generates scanning datadefining a tomographic X-ray image of the object; a processor executingprogrammatic instructions wherein said executing processor analyzes thescanning data to extract at least one parameter of the tomographic X-rayimage and wherein said processor is configured to determine if saidobject is a bottle containing a liquid, a narcotic, tobacco, fire-arms,currency, sharp objects, or any other illicit object. The processorexecutes programmatic instructions to allocate the object to one of aplurality of categories on the basis of the at least one parameter. Theprogrammatic instructions comprise at least one parameter extractor foridentifying at least one predefined feature in the tomographic X-rayimage wherein said predefined feature comprises a plurality of low levelparameters of the X-ray image. Such low level parameters can includebasic dimension, density, size, and shape information.

The programmatic instructions comprise at least one decision tree forconstructing high level parameters based upon the identified low levelparameters of the X-ray image. The high level parameters includedeterminations of the type of object, such as a bottle, repeatingpatterns, arrays of structures, among other defining variables. TheX-ray scanning system further comprises a database search tool formapping the constructed high level parameters of the X-ray image topredefined data stored in a database. The X-ray scanning system furthercomprises an alarm system for activating an alarm based on a result ofsaid mapping, wherein said alarm defines an object as being a potentialthreat or not a potential threat. The at least one parameter extractoris configured to operate on one 2-dimensional images, 3-dimensionalimages or sinogram image data.

In various embodiments, the methods of the present invention describedabove are provided as a computer readable medium tangibly embodying aprogram of machine-readable instructions executable by a processor.

BRIEF DESCRIPTION OF THE INVENTION

Embodiments of the present invention will now be described by way ofexample only with reference to the accompanying drawings in which:

FIG. 1 is a longitudinal section of a real time tomography securityscanning system according to a first embodiment of the invention;

FIG. 1 a is a perspective view of an X-ray source of the system of FIG.1;

FIG. 2 is a plan view of the system of FIG. 1;

FIG. 3 is a schematic side view of the system of FIG. 1;

FIG. 4 is a schematic diagram of a data acquisition system forming partof the system of FIG. 1;

FIG. 5 is a schematic diagram of a threat detection system forming partof the system of FIG. 1;

FIG. 6 is a schematic diagram of a baggage sorting system according toan embodiment of the invention including the scanning system of FIG. 1;

FIG. 7 is a schematic diagram of a baggage sorting system according to afurther embodiment of the invention;

FIG. 8 a is a schematic diagram of baggage sorting systems according tofurther embodiments of the invention;

FIG. 8 b is another schematic diagram of baggage sorting systemsaccording to further embodiments of the invention;

FIG. 8 c is another schematic diagram of baggage sorting systemsaccording to further embodiments of the invention;

FIG. 9 is a schematic diagram of a networked baggage sorting systemaccording to a further embodiment of the invention;

FIG. 10 is a schematic plan view of a stand-alone scanning systemaccording to a further embodiment of the invention;

FIG. 11 is a schematic side view of the system of FIG. 10;

FIG. 12 is a schematic side view of a modular scanning system accordingto a further embodiment of the invention;

FIG. 13 is a diagram of an X-ray scattering event;

FIG. 14 is a longitudinal section through a security scanning systemaccording to a further embodiment of the invention;

FIG. 15 is a further longitudinal section through the system of FIG. 14showing how different scatter events are detected;

FIG. 16 is a transverse section through the system of FIG. 14;

FIG. 17 is a schematic diagram of a data acquisition system of thescanning system of FIG. 14;

FIG. 18 is a partial view of a dual energy scanner according to afurther embodiment of the invention;

FIG. 19 is a further partial view of the scanner of FIG. 18;

FIG. 20 is a schematic view of a dual energy X-ray source of a furtherembodiment of the invention;

FIG. 21 is a schematic view of a detector array of a scanner accordingto a further embodiment of the invention;

FIG. 22 is a schematic view of a detector array of a scanner accordingto a further embodiment of the invention;

FIG. 23 is a circuit diagram of a data acquisition circuit of theembodiment of FIG. 21; and

FIG. 24 is a circuit diagram of a data acquisition circuit of a furtherembodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Referring to FIGS. 1 to 3, a concourse baggage scanning system 6comprises a scanning unit 8 comprising a multi-focus X-ray source 10 andX-ray detector array 12. The source 10 comprises a large number ofsource points 14 in respective spaced locations on the source, andarranged in a full 360.degree circular array around the axis X-X of thesystem. It will be appreciated that arrays covering less than the full360.degree. angle can also be used.

Referring to FIG. la, the X-ray source 10 is made up of a number ofsource units 11 which are spaced around the scanning region 16 in asubstantially circular arrangement, in a plane perpendicular to thedirection of movement of the conveyor. Each source unit 11 comprises aconductive metal suppressor 13 having two sides and an emitter element15 extending along between the suppressor sides. A number of gridelements in the form of grid wires 17 are supported above the suppressor13 perpendicular to the emitter element 15. A number of focusingelements in the form of focusing wires 19 are supported in another planeon the opposite side of the grid wires to the emitter element. Thefocusing wires 19 are parallel to the grid wires 17 and spaced apartfrom each other with the same spacing as the grid wires, each focusingwire 19 being aligned with a respective one of the grid wires 17.

The focusing wires 19 are supported on two support rails 21 which extendparallel to the emitter element 15, and are spaced from the suppressor13. The support rails 21 are electrically conducting so that all of thefocusing wires 19 are electrically connected together. One of thesupport rails 21 is connected to a connector 23 to provide an electricalconnection for the focusing wires 19. Each of the grid wires 17 extendsdown one side of the suppressor 12 and is connected to a respectiveelectrical connector 25 which provide separate electrical connectionsfor each of the grid wires 17.

An anode 27 is supported above the grid wires 17 and focusing wires 19.The anode 27 is formed as a rod, typically of copper with tungsten orsilver plating, and extends parallel to the emitter element 15. The gridand focusing wires 17, 19 therefore extend between the emitter element15 and the anode 27. An electrical connector 29 provides an electricalconnection to the anode 27.

The grid wires 17 are all connected to a negative potential, apart fromtwo which are connected to a positive potential. These positive gridwires extract a beam of electrons from an area of the emitter element 15and, with focusing by the focusing wires 19, direct the electron beam ata point on the anode 27, which forms the X-ray source point for thatpair of grid wires. The potential of the grid wires can therefore beswitched to select which pair of grid wires is active at any one time,and therefore to select which point on the anode 27 is the active X-raysource point at any time.

The source 10 can therefore be controlled to produce X-rays from each ofthe source points 14 in each of the source units 11 individually and,referring back to FIG. 1, X-rays from each source point 14 are directedinwards through the scanning region 16 within the circular source 10.The source 10 is controlled by a control unit 18 which controls theelectrical potentials applied to the grid wires 17 and hence controlsthe emission of X-rays from each of the source points 14. Other suitableX-ray source designs are described in WO 2004/097889.

The multi-focus X-ray source 10 allows the electronic control circuit 18to be used to select which of the many individual X-ray source points 14within the multi-focus X-ray source is active at any moment in time.Hence, by electronically scanning the multi-focus X-ray tube, theillusion of X-ray source motion is created with no mechanical partsphysically moving. In this case, the angular velocity of source rotationcan be increased to levels that simply cannot be achieved when usingconventional rotating X-ray tube assemblies. This rapid rotationalscanning translates into an equivalently speeded up data acquisitionprocess and subsequently fast image reconstruction.

The detector array 12 is also circular and arranged around the axis X-Xin a position that is slightly offset in the axial direction from thesource 10. The source 10 is arranged to direct the X-rays it producesthrough the scanning region 16 towards the detector array 12 on theopposite side of the scanning region. The paths 18 of the X-ray beamstherefore pass through the scanning region 16 in a direction that issubstantially, or almost, perpendicular to the scanner axis X-X,crossing each other near to the axis. The volume of the scanning regionthat is scanned and imaged is therefore in the form of a thin sliceperpendicular to the scanner axis. The source is scanned so that eachsource point emits X-rays for a respective period, the emitting periodsbeing arranged in a predetermined order. As each source point 14 emitsX-rays, the signals from the detectors 12, which are dependent on theintensity of the X-rays incident on the detector, are produced, and theintensity data that the signals provide are recorded in memory. When thesource has completed its scan the detector signals can be processed toform an image of the scanned volume.

A conveyor belt 20 moves through the imaging volume, from left to right,as seen in FIG. 1, parallel to the axis X-X of the scanner. X-rayscatter shields 22 are located around the conveyor belt 20 upstream anddownstream of the main X-ray system to prevent operator dose due toscattered X-rays. The X-ray scatter shields 22 include lead rubber stripcurtains 24 at their open ends such that the item 26 under inspection isdragged through one curtain on entering, and one on leaving, theinspection region. In the integrated system shown, the main electroniccontrol system 18, a processing system 30, a power supply 32 and coolingracks 34 are shown mounted underneath the conveyor 20. The conveyor 20is arranged to be operated normally with a continuous scanning movementat constant conveyor speed, and typically has a carbon-fiber frameassembly within the imaging volume.

Referring to FIG. 4 the processing system 30 includes an electronic dataacquisition system and real-time image reconstruction system. The X-raydetector array 12 comprises banks of individual X-ray detectors 50configured in a simple linear pattern (e.g. 1.times.16). Multiple ringpatterns (e.g. 8.times.16) are also possible. Each detector 50 outputs asignal dependent on the intensity of the X-rays it detects. Amultiplexing block 52 multiplexes the output data signals from each ofthe input X-ray detectors 50, performs data filtering, gain and offsetcorrections and formats the data into a high-speed serial stream. Aselection block 53 takes input from all of the multiplexing blocks 52and selects just the part of the entire X- ray data that is required forthe image reconstruction. The selection block 53 also determines theun-attenuated X-ray beam intensity, Io, for the appropriate X-ray sourcepoint (which will vary for every X-ray source point within themulti-focus X-ray tube), processes the X-ray intensity data, Ix, fromthe multiplexing block 52 by forming the result log_(o)(Ix/Io) and thenconvolves this with a suitable 1-D filter. The resulting projection datais recorded as a sinogram, in which the data is arranged in an arraywith pixel number along one axis, in this case horizontally, and sourceangle along another axis, in this case vertically.

Data is then passed from the selection block 53 in parallel to a set ofback projection-summation processor elements 54. The processor elements54 are mapped into hardware, using look-up tables with pre-calculatedcoefficients to select the necessary convolved X-ray data and weightingfactors for fast back projection and summation. A formatting block 55takes the data representing individual reconstructed image tiles fromthe multiple processor elements 54 and formats the final output imagedata to a form suitable for generating a suitably formatted threedimensional image on a display screen. This output can be generated fastenough for the images to be generated in real time, for viewing in realtime or off-line, hence the system is termed a real time tomography(RTT) system.

In this embodiment the multiplexing block 52 is coded in software, theselection block 53 and formatting block 55 are both coded in firmware,and the processor elements mapped in hardware. However, each of thesecomponents could be either hardware or software depending on therequirements of the particular system.

Referring to FIG. 5 each of the final output images for each baggageitem is then processed by a threat detection processor 60 within theprocessing system 30 which is arranged to determine whether the imagedbaggage item represents a threat. In the threat detection processor 60,input X-ray tomographic image data 62 is passed in to a set of low-levelparameter extractors 63 (level 1). The parameter extractors 63 identifyfeatures in the image such as areas of constant grey level, texture andstatistics. Some of the extractors work on the data for individual 2dimensional images or slices, some work on the 3 dimensional images, andsome work on the sinogram data. Where possible, each extractor works inparallel on the same set of input data, and each extractor is arrangedto perform a different processing operation and to determine a differentparameter. At the end of the processing, the parameters determined bythe parameter extractors 63 are passed up to a set of decision trees 64(level 2). Details of the parameters extracted are given below. Thedecision trees 64 each take a number (typically all) of the low levelparameters and construct respective higher level information, such asinformation regarding contiguous volumes, with associated statistics. Atthe top level (level 3), a database searcher 65 maps the higher levelparameters produced at level 2 into a ‘red’ probability Pr(threat) ofthere being a threat present and a ‘green’ probability Pr(safe) of theitem under inspection being safe. These probabilities are used by theprocessing system 30 to allocate the scanned item to an appropriatesafety category, and to produce an automatic sorting control output.This automatic sorting control output can be either a first ‘green’output indicating that the item is allocated to a clear category, asecond ‘red’ output indicating that the item is allocated to a ‘notclear’ category, or a third ‘amber’ output indicating that the automaticsorting cannot be carried out with sufficient reliability to allocatedthe item to the ‘clear’ or the ‘not clear’ category. Specifically ifPr(safe) is above a predetermined value, (or Pr(threat) is below apredetermined value) then the automatic sorting output will be producedhaving a first signal form, indicating that the item should be allocatedto the green channel. If Pr(threat) is above a predetermined value, (orPr(safe) is below a predetermined value) then the automatic sortingoutput will be produced having a second signal form, indicating that theitem should be allocated to the red channel. If Pr(threat) (or Pr(safe))is between the two predetermined values, then the automatic sortingoutput is produced having a third signal form, indicating that the itemcannot be allocated to either the red or green channel. Theprobabilities can also be output as further output signals.

The parameters that will be determined by the parameter extractors 63generally relate to statistical analysis of pixels within separateregions of the 2-dimensional or 3-dimensional image. In order toidentify separate regions in the image a statistical edge detectionmethod is used. This starts at a pixel and then checks whether adjacentpixels are part of the same region, moving outwards as the region grows.At each step an average intensity of the region is determined, bycalculating the mean intensity of the pixels within the region, and theintensity of the next pixel adjacent to the region is compared to thatmean value, to determine whether it is close enough to it for the pixelto be added to the region. In this case the standard deviation of thepixel intensity within the region is determined, and if the intensity ofthe new pixel is within the standard deviation, then it is added to theregion. If it is not, then it is not added to the region, and thisdefines the edge of the region as being the boundary between pixels inthe region and pixels that have been checked and not added to theregion.

Once the image has been divided into regions, then parameters of theregion can be measured. One such parameter is a measure of the varianceof the pixel intensity within the region. If this is high this might beindicative of a lumpy material, which might for example be found in ahome-made bomb, while if the variance is low this would be indicative ofa uniform material such as a liquid.

Another parameter that is measured is the skewedness of the distributionof pixel value within the region, which is determined by measuring theskewedness of a histogram of pixel values. A Gaussian, i.e. non-skewed,distribution indicates that the material within the region is uniform,whereas a more highly skewed distribution indicates non-uniformities inthe region.

As described above, these low-level parameters are passed up to thedecision trees 64, where higher level information is constructed andhigher level parameters are determined. One such higher level parameteris the ratio of the surface area to the volume of the identified region.Another is a measure of similarity, in this case cross-correlation,between the shape of the region and template shapes stored in thesystem. The template shapes are arranged to correspond to the shape ofitems that pose a security threat, such as guns or detonators. Thesehigh level parameters are used as described above to determine a levelif threat posed by the imaged object.

Referring to FIG. 6 an in-line real time tomography baggage sortingsystem comprises the scanning system 6 of FIG. 1 with the conveyor 20passing through it. Downstream of the scanning system 6 a sorting device40 is arranged to receive articles of baggage from the conveyor 20 andmove them onto either a clear or ‘green’ channel conveyor 42 or a notclear or ‘red’ channel conveyor 44. The sorting device 40 is controlledby the automatic sorting output signals via a control line 46 from theprocessing system 30, which are indicative of the decision of theprocessing system 30 as to whether the item is clear or not, and also bysignals from a workstation 48 to which it is connected via line 45. Theimages from the scanning system 6 and signals from the processing system30, indicative of the red and green probabilities and the nominaldecision of the processing system 30, are also fed to the workstation48. The workstation is arranged to display the images on a screen 47 sothat they can be viewed by a human operator, and also to provide adisplay indicative of the green and red probabilities and the nominalautomatic sorting decision. The user at the workstation can review theimages and the probabilities, and the automatic sorting output, anddecide whether to accept or override the decision of the scanningsystem, if that was to allocate the item to the red or green category,or to input a decision if the scanning system decision was to allocatethe item to the ‘amber’ category. The workstation 48 has a user input 49that enables the user to send a signal to the sorting device 40 whichcan be identified by the sorting device as over-riding the decision ofthe scanning system. If the over-riding signal is received by thesorting device, then the sorting device does over-ride the decision ofthe scanning system. If no over-ride signal is received, or indeed if aconfirming signal is received from the workstation confirming thedecision of the scanning system, then the sorting device sorts the itemon the basis of the decision of the scanning system. If the sortingsystem receives an amber' signal from the scanning system relating to anitem, then it initially allocates that item to the ‘red’ category to beput into the red channel. However, if it receives an input signal fromthe workstation before it sorts the item indicating that it should be inthe ‘green’ category, then it sorts the item to the green channel.

In a modification to the system of FIG. 6, the sorting can be fullyautomatic, with the processing system giving one of just two sortingoutputs, ‘clear’ and ‘not clear’, allocating the item to either thegreen or the red channel. It would also be possible for the processingsystem to determine just one probability Pr(threat) with one thresholdvalue and allocate the item to one of the two categories depending onwhether the probability is above or below the threshold. In this casethe allocation would still be provisional and the operator would stillhave the option of overriding the automatic sorting. In a furthermodification the automatic category allocation of the scanning system isused as the final allocation, with no user input at all. This provides afully automated sorting system.

In the system of FIG. 6, the scan speed is matched to the conveyorvelocity, so that the baggage can be moved at a constant velocity from aloading area where it is loaded onto the conveyor 20, through thescanning system 6, and on to the sorting device 40. The conveyor 20extends for a distance L, between the exit of the scanning system 6 andthe sorting device 40. During the time that a baggage item takes totravel the distance L on the conveyor 20, an operator can view the imagedata of the item under inspection, and the initial category allocationdetermined by the scanning system, and confirm or reject the automateddecision of the RTT system. Typically the baggage would then be eitheraccepted into the Clear channel and passed forward ready fortransportation or rejected into the Not Cleared channel for furtherinvestigation.

In this RTT multi-focus system, the RTT scanning unit 8 is able tooperate at full baggage belt speed, and hence no baggage queuing orother divert mechanism is required for optimal system operation. Inintegrated systems such as this, the limited throughput capability ofconventional rotating source systems is a significant constraint. Oftenthis means placing multiple conventional CT machines in parallel, andusing sophisticated baggage handling systems to switch the item forinspection to the next available machine. This complexity can be avoidedwith the arrangement of FIG. 6.

Referring to FIG. 7 a second embodiment of the invention comprises aredundant system in which two RTT scanning systems 70, 72 are located inseries on the same conveyor 74 such that if one system were to be takenout of service, then the other could continue to scan baggage. In eithercase, the conveyor belt 74 would continue to run through both scanningsystems 70, 72 at standard operating belt speed.

Referring to FIG. 8 a in a third embodiment there is provided a morecomplex redundant system in which two RTT systems 82, 84 are operated inparallel. A first main incoming conveyor 86 brings all items to besorted to a first sorting device 88 which can transfer items onto eitherone of two further conveyors 90, 92. Each of these two conveyors 90, 92passes through a respective one of the scanning systems 82, 84, whichwill scan the items and enable a decision to be made as to whether toclear the item or not. A further sorting device 94, 96 is provided oneach of the two conveyors 90, 92 which is arranged to sort the baggageonto a common ‘green channel’ conveyor 98 for onward transportation, ora ‘red channel’ conveyor 100 if it is not cleared, where it can undergofurther investigation. In this configuration, it is possible to run theinput conveyor 86, and the ‘green channel’ conveyor at a higher speedthan the RTT conveyor speed, typically up to twice the speed. Forexample in this case the main incoming conveyor 86 and the common ‘greenchannel’ conveyor move at a speed of 1 m/s whereas the scanningconveyors 82, 84 travel at half that speed, i.e. 0.5 m/s. Of course thesystem can be expanded with more parallel RTT systems, with the ratio ofthe speed of the main incoming conveyor to that of the scanner conveyorsbeing equal to, or substantially equal to, the number of parallelscanners, although the sorting devices may become unreliable at morethan about 1 m/s main conveyor speed.

Referring to FIG. 8 b, in a further embodiment a baggage sorting systemcomprises a number of RTT scanners 81 b, 82 b, 83 b, typically up toabout 60 in one system, each associated with a respective check-in desk.A sorting device 84 b, 85 b, 86 b is associated with each RTT scanner,and baggage is conveyed on a conveyor from each RTT scanner to itsassociated sorting device. Each sorting device 84 b, 85 b, 86 b sortsthe baggage, in response to signals from its scanner, onto either acommon clear channel conveyor 88 b, or a common reject channel conveyor87 b. A further backup RTT scanner 89 b is provided on the rejectchannel conveyor 87 b, with an associated sorting device 90 b, that canleave baggage on the reject channel conveyor 87 b, or transfer it to theclear channel conveyor 88 b.

Under normal operation, each of the primary scanners 81 b, 82 b, 83 bsorts the baggage, and the backup or redundant scanner 89 b simplyprovides a further check on items sorted into the reject channel. Ifthat scanner determines that an item of baggage represents no, or asufficiently low threat, then it transfers it to the clear channel. Ifone of the primary scanners is not functioning or has a fault, then itsassociated sorting device is arranged to sort all baggage from thatscanner to the reject channel. Then, the back-up scanner 89 b scans allof that baggage and controls sorting of it between the clear and rejectchannels. This enables all the check-in desks to continue to functionwhile the faulty scanner is repaired or replaced.

Referring to FIG. 8 c, in a further embodiment, baggage from each of thecheck-in desks is transferred via a plurality of separate conveyors ontoa central loop or carousel 81 c, on which it circulates continuously. Anumber of sorting devices 82 c, 83 c, 84 c are each arranged to transferitems of baggage from the loop 81 c to a respective conveyor leading toa respective RTT scanner 85 c, 86 c, 87 c. The sorting devices 82 c, 83c, 84 c are controlled by the scanners to control the rate at whichbaggage items are fed to each of the scanners. From the scanners,conveyors transfer all of the baggage items to a common exit conveyor 88c leading to a further sorting device 89 c. This is controlled by all ofthe scanners to sort each of the baggage items between a clear channel90 c and a reject channel 91 c.

In order to track the movement of each item of baggage, each item isgiven a 6-digit ID, and its position on the conveyor recorded when itfirst enters the system. The scanners can therefore identify which itemof baggage is being scanned at any one time, and associate the scanningresults with the appropriate item. The sorting devices can thereforealso identify the individual baggage items and sort them based on theirscanning results. The number of scanners and the speeds of the conveyorsin this system are arranged such that, if one of the scanners is notfunctioning, the remaining scanners can process all of the baggage thatis being fed onto the loop 81 c from the check-in desks.

In a modification to this embodiment, the sorting devices 82 c, 83 c, 84c that select which items are transferred to each scanner are notcontrolled by the scanners, but are each arranged to select items fromthe loop 81 c so as to feed them to the respective scanner at apredetermined rate.

Referring to FIG. 9 a networked system according to a further embodimentcomprises three scanning systems 108 similar to that of FIG. 6, and fouroperator workstations 148. The video image outputs from the three RTTscanning systems 108 are connected via respective high bandwidthpoint-to-point video links to real time disk arrays 109 which providingtransient storage for the raw image data, to a redundant video switch110. The disk arrays 109 are in turn connected to each of theworkstations 148. The video switch 110 is therefore able to transmit theraw video image output from each of the scanning systems 108 from itstemporary storage, to any one of the workstations 148, where it can beused to create 3-dimensional video images which can be viewed off-line.The outputs from the scanning system for the red/green probabilitysignals and the automatic sorting allocation signals are connected to aredundant conventional Ethernet switch 112, which is also connected toeach of the workstations. The Ethernet switch is arranged to switch eachof the probability signals and the sorting allocation signals to thesame workstation 148 as the associated video signal.

This allows image data from the multiple machines together with theautomatic allocation and probabilities assigned to the allocation, to beswitched through to the bank of operator workstations 148 where anoperator can both monitor the performance of the baggage inspectionsystem and determine the destination of baggage assigned an amber threatlevel. Alternatively, a networked system comprises a single scanningsystem 108 connected to a server and a workstation 148. The video imageoutput from the scanning system 108 is connected to a real time diskarray 109, which provides transient storage for the raw image data. Thedisk array 109 is in turn connected to the workstation 148. Theprobability signal and allocation signal outputs are sent to theworkstation 148 together with the associated video image output to bemonitored by an operator. The networked single scanning system may bepart of a networked system with multiple scanning systems.

Referring to FIGS. 10 and 11, in a further embodiment an in-line scannerhas a conveyor belt 160 just as long as the main scatter shields 162. Insuch standalone system configurations, the item for inspection is placedonto the conveyor belt 160 and the item loaded into the system. The itemis then scanned through the scanner machine 164 and images aregenerated. Often, in conventional systems, the item is pre-screened witha simple transmission X-ray system to identify likely threat areas priorto computed tomography screening of selected planes in the object. Suchapplications are simple for a real-time multi-focus system to cope with.Here, no pre-screening would be used and a true three-dimensional imageof the complete item would be obtained.

In some embodiments the locus of source points in the multi-focus X-raysource will extend in an arc over an angular range of only 180 degreesplus the fan beam angle (typically in the range 40 to 90 degrees). Thenumber of discrete source points is advantageously selected to satisfythe Nyquist sampling theorem. In some embodiments, as in that of FIG. 1,a complete 360 degree ring of source points is used. In this case, thedwell-time per source point is increased over a 180+ fan beamconfiguration for a given scan rate and this is advantageous inimproving reconstructed image signal-to-noise ratio.

The scanner system of FIG. 1 is an integrated scanner system, in thatthe control, processing, power supply, and cooling units 18, 30, 32, 34are housed in a unit with the scanning system 8 and the screening 22.Referring to FIG. 12, in a further embodiment there is provided amodular system in which some, or all, of the control, processing, powersupply, and cooling racks 218, 230, 232, 234 are located remotely fromthe scanning unit 208 comprising multi-focus X-ray source and sensorarray. It is advantageous to use a modular design to facilitate easyinstallation, particularly in baggage handling hall environments, wheresystems may be suspended from the ceiling or in regions with restrictedaccess. Alternatively, a complete system can be configured as anintegrated unit with the sub-assembly units co-located within a singlehousing.

In some embodiments, including that of FIG. 1, a single X-ray detectorring is used. This is inexpensive to construct and provides adequatesignal-to-noise performance even at high image scanning rates with asimple fan-beam image reconstruction algorithm. In other embodiments(particularly for large image reconstruction circle diameter) it ispreferable to use a multi-ring sensor array with a plurality of circularor part-circular groups of sensors arranged adjacent to each other,spaced along the axis of the system offset from the source. This enablesa more complex cone-beam image reconstruction algorithm to be used inthe processing system. The use of a multi-ring sensor increasesdwell-time per source point resulting in larger integrated signal sizeand consequent improvement in signal-to-noise ratio in the reconstructedimage.

Central to the design of the embodiments described above, which use amulti-focus X-ray source based computed tomography system, is therelationship between the angular rotational speed of the source and thevelocity of the conveyor system passing through the scanner. In thelimit that the conveyor is stationary, the thickness of thereconstructed image slice is determined entirely by the size of theX-ray focus and the area of the individual elements of the X-raydetector array. As conveyor speed increases from zero, the object underinspection will pass through the imaging slice during rotation of theX-ray beam and an additional blurring will be introduced into thereconstructed image in the direction of the slice thickness. Ideally,the X-ray source rotation will be fast compared to the conveyor velocitysuch that blurring in the slice thickness direction will be minimized.

A multi-focus X-ray source based computed tomography system for baggageinspection provides a good ratio of angular source rotational speed tolinear conveyor speed for the purposes of high probability detection ofthreat materials and objects in the item under inspection. As anexample, in the embodiment of FIG. 1, the conveyor speed is 0.5 m/s asis common in airport systems. The source can achieve 240 sourcerotations about the conveyor per second, so the object under inspectionwill move a distance of 2.08 mm through the imaging slice during thescan. In a conventional system with source rotation of 4 revolutions persecond, the object under inspection will move a distance of 62.5 mmthrough the imaging slice during the scan at the same belt speed.

The primary goal of an inspection system for detection of threatmaterials is to detect accurately the presence of threat materials andto pass as not suspect all other materials. The larger the blurring inthe slice direction that is caused by conveyor motion during a scan, thegreater the partial volume artifact in the reconstructed image pixel andthe less accurate the reconstructed image density. The poorer theaccuracy in the reconstructed image density, the more susceptible thesystem is to provide an alarm on non-threat materials and to not raisean alarm on true threat materials. Therefore, a real-time tomography(RTT) system based on multi-focus X-ray source technology can provideconsiderably enhanced threat detection capability at fast conveyorspeeds than conventional mechanically rotated X-ray systems.

Due to the use of an extended arcuate anode in a multi-focus X-raysource, it is possible to switch the electron source such that it jumpsabout the full length of the anode rather than scanning sequentially toemulate the mechanical rotation observed in conventional computedtomography systems. Advantageously, the X-ray focus will be switched tomaximize the distance of the current anode irradiation position from allprevious irradiation positions in order to minimize the instantaneousthermal load on the anode. Such instantaneous spreading of the X-rayemission point is advantageous in minimizing partial volume effect dueto conveyor movement so further improving reconstructed pixel accuracy.

The high temporal resolution of RTT systems allows a high level ofaccuracy to be achieved in automated threat detection. With this highlevel of accuracy, RTT systems can be operated in unattended mode,producing a simple two-state output indication, with one statecorresponding to a green or clear allocation and the other to a red ornot clear allocation. Green bags are cleared for onward transport. Redbags represent a high level of threat and should be reconciled with thepassenger and the passenger barred from traveling.

Further embodiments of the invention will now be described in which datarelating to the scattering of X-rays as well as that relating totransmitted X-rays is recorded and used to analyze the scanned baggageitems.

Referring to FIG. 13 when a beam 300 of X-rays passes through an object302, some of the X-rays are transmitted straight through it, and exitthe object traveling in the same direction as they entered it. Some ofthe X-rays are scattered through a scattering angle θ, which is thedifference between the direction in which they enter the object and thedirection in which they leave it. As is well known there are two typesof scattering that occur: coherent or Bragg scattering, which isconcentrated around scattering angles of 5 degrees, typically in therange 4 degrees to 6 degrees, and incoherent or Compton scattering inwhich the X-ray is scattered through larger angles. Bragg scatteringincreases linearly with the atomic number of the object and obeys theformula:

nλ=2d sin θ

where n is an integer, λ is the wavelength of the X-ray, and d is theinter-atomic distance in the object.

Therefore the amount of Bragg scattering gives information about theatomic structure of the object. However, it does not vary smoothly withatomic number.

The amount of Compton scattering is dependent on, and varies smoothlywith, the electron density of the object, and therefore the amount ofscattering at higher scatter angles gives information about the electrondensity of the object, and hence about its atomic number.

Referring to FIG. 14 a security scanning system according to a furtherembodiment of the invention comprises a multi-focus X-ray source 410which is the same as that of FIG. 1, and a circular detector array 412and conveyor 420 that are also the same as those of FIG. 1. However, inthis embodiment, the system comprises a further cylindrical array ofdetectors 422 which also extends around the conveyor at the same radiusas the circular detector array 412 but on the other side axially of thesource 410. Whereas the circular detector array is arranged to detectX-rays transmitted through the object 426, the cylindrical detectorarray 422 is arranged to detect X-rays scattered in the object. Thescatter detector array 422 is made up of a number of circular arrays orrings 422 a, 422 b of detectors, and the detectors in each ring areequally spaced around the conveyor so that they are arranged in a numberof straight rows extending in the axial direction of the scanner.

The detectors in the scatter detector array 422 are energy resolvingdetectors such that individual X-ray interactions with each detectorproduce a detector output that is indicative of the energy of the X-ray.Such detectors can be fabricated from wide bandgap III-V or II-IVsemiconductor materials such as GaAs, HgI, CdZnTe or CdTe, a narrow gapsemiconductor such as Ge, or a composite scintillation detector such asNaI(Ti) with photomultiplier tube readout.

Referring to FIG. 15, a collimator 428 is provided in front of thescattering detectors 422. The collimator 428 provides a barrier thatprevents X-rays from reaching each detector unless it comes from aparticular receiving direction. For each detector in the array 422, thereceiving direction passes through the central longitudinal axis X-X ofthe scanner, as can be seen in FIG. 16. However, the receiving directionis not perpendicular to the axis X-X, but is inclined at about 5.degree.to the plane of the detector rings 422 a, 422 b in the direction towardsthe source 410, as can be seen in FIG. 15.

Referring to FIG. 15 it will be appreciated that X-rays incident on anyone of the detectors of the array 422 must have been scattered from arespective small sub-volume within the thin imaged volume that lies bothin the path of the X-ray beam and in the line of the receiving directionfrom the detector 422. For any coherently scattered X-rays, the axialposition of the detector that detects it will be determined by thedistance from the active X-ray source point at which the scatteringoccurred. Detectors nearest the source 410 in the axial direction willdetect X-rays scattered furthest from the active X-ray source point. Forexample X-rays scattered from the point x, which is nearest the activeX-ray source point 410 a, will be detected by a detector further fromthe source 410 than X-rays scattered from the point z which is furtherfrom the active X-ray source point. Therefore, at any one time, when theactive X-ray source point can be identified, the axial position of thedetector which detects the scattered X-ray can be used to determine theposition of the scattering along the X-ray beam direction.

It will also be appreciated from FIG. 15 that, for this system to work,it is important that the X-ray beam should be narrowly focused in theaxial direction of the scanner. Spreading of the beam in the transversedirection, e.g. use of a fan beam spread in the transverse directionwill still allow this positioning of coherent scattering events.

Referring to FIG. 16, because the collimator 428 is directed towards theaxis of the scanner, X-rays from an active source point 410 a thatundergo coherent scattering will only be detected by the row ofdetectors 422 a that is on the opposite side of the scanner axis to theactive source point, and possibly one or more of the rows close to it oneither side depending on how narrowly focused the collimator is. IfX-rays are confined to a straight narrow ‘pencil’ beam, then any X-raysthat are scattered incoherently through larger angles will not bedetected at all as they will be cut off by the collimator 428. Anexample of such an X-ray is shown by arrow ‘a’ in FIG. 16. However, if afan beam of X-rays is produced from the active source point 410 a, thatis spread out through the imaging volume slice in the directionperpendicular to the scanner axis, then X-rays directed further awayfrom the scanner axis can undergo incoherent scattering and reachdetectors to either side of the row 422 a opposite the active sourcepoint. Examples of such X-rays are shown by the arrows b and c. It willbe noted that, to reach any detector 422 b, the scattering event musttake place in the plane passing through the scanner axis and thatdetector 422 b. This means that, for a given active source point and aparticular detector, the position of the scattering event of a detectedX-ray can be identified as being in the plane passing through thescanner axis and that detector. If the exact position of the scatteringevent is to be determined then other information is needed. For exampleif information regarding the position of objects within the imagingvolume is available, for example from tomographic imaging data, then thescattering can be associated with the most likely object as will bedescribed in more detail below.

From the Bragg scattering data, for each detected scattering event, thecombination of the X-ray energy and the scatter angle can be used todetermine the inter-atomic distance d of the material in which thescattering event took place. In practice, the scatter angle can beassumed to be constant, and the energy used to distinguish betweendifferent materials. For the Compton scattering, the level of scatteringfrom each volume of the scanning volume gives an indication of thedensity of the material in that volume. The ratio of Compton to coherentscatter can also be determined and used as a further parameter tocharacterize the material of the imaged object.

Due to the short dwell time for each X-ray source point, the number ofdetected scattered X-rays for each source point will always be very low,typically less than five. In order to form a reasonable coherent scattersignal it is necessary to collect scatter data for all source pointswithin a tomographic scan and then accumulate the results for eachsub-volume of the imaging volume. For a scanner with 500 source points,and an average of one coherent diffraction scatter result per sub-volumeper scan, then following accumulation of the set of data, eachsub-volume will have 500 results associated with it, corresponding to500 scattering events within that sub-volume. A typical sub-volumeoccupies an area within the imaging plane of a few square centimeters,with a volume thickness of a few millimeters.

Referring to FIG. 17, the data acquisition system arranged to accumulatedata from the scatter detector array 422 of the scanner of FIGS. 14 to16 comprises a multi-channel analyzer 500 associated with each of thedetectors 422. Each MCA 500 is arranged to receive the output signalsfrom the detector, and allocate each X-ray detected to one of a numberof X-ray energy ranges or channels, and output a signal indicative ofthe energy range in which the detected X-ray falls. A multiplexer 502 isarranged to receive the outputs from each of the MCAs 500. A look-uptable 504 is also provided which has entries in it that, for a givensource point and detector, identify the sub-volume within the imagingvolume in which the X-ray was scattered. The system further comprises animage memory 506 which includes a number of memory areas 508, each ofwhich is associated with a respective sub-volume within the scannerimaging plane.

Data is loaded into each memory area 508 automatically by themultiplexer 502 under the direction of the look up table 504. The lookup table is loaded with coefficients prior to scanning that map eachcombination of detector 422 and MCA 500 to a respective image location508, one look up table entry per X-ray source position. Those pixels,i.e. detectors 422, that are in the forward direction, i.e.substantially in the direction that the photon is traveling from thesource prior to any interaction, are assumed to record coherent scatterphotons at small beam angles of about 4-6 degrees. Those pixels 422 thatare not in the forward direction are assumed to record incoherentscattered photons due to the Compton scattering effect. Hence, the imagememory 506 is actually “three dimensional”—two dimensions representlocation in the image while the third dimension holds scattered energyspectra for both coherent (lo 8-bits) and incoherent scattering (hi 8bits). The look up table 504 will also instruct the multiplexer 502 asto the type of data that is being collected for each MCA 500 at eachprojection so that the appropriate memory space is filled.

Once the scatter data has been collected for a given scan, the data istransferred to and synchronized, by a projection sequencer 510, with themain RTT data acquisition system 512, which is described above withreference to FIG. 4. Hence the reconstructed image data and scatter dataare passed through simultaneously to the threat detection system, whichcan use it to determine suitable parameters for analysis.

For each scan, the tomographic image data from the transmissiondetectors 412 produces data relating to the X-ray attenuation for eachpixel of the image, which in turn corresponds to a respective sub-volumeof the tomographic imaging volume. This is obtained as described abovewith reference to FIG. 4. The data from the scatter detectors 422provides, as described above, data relating to the amount of coherentscattering within each sub-volume, and data relating to the amount ofincoherent scattering within each sub-volume. This data can therefore beanalyzed in a threat detection processor similar to that of FIG. 5. Inthis case the parameters of the data which are extracted can relate tothe image data or the scatter data or combinations of two or more typesof data. Examples of parameters that are extracted from the data are theratio of coherent to incoherent scatter, material types as determinedfrom coherent scatter data, material density as determined fromincoherent scatter data, correlation of CT image pixel values withscatter data. Also parameters for the scatter data corresponding tothose described above for the transmission data can also be determined.

Referring to FIG. 18, in a further embodiment of the invention thetransmission detectors 512 that are used to generate the tomographicimage data are arranged to measure the X-ray transmission over differentenergy ranges. This is achieved by having two sets of detectors 512 a,512 b, each forming a ring around the conveyor. The two sets are atdifferent axial locations along the direction of travel of the conveyor,in this case being adjacent to each other in the axial direction. Thefirst set 512 a has no filter in front of it, but the second set 512 bhas a metal filter 513 placed between it and the X-ray source 510. Thefirst set of detectors 512 a therefore detects transmitted X-rays over abroad energy range, and the second set 512 b detects X-rays only in anarrower part of that range at the high energy end.

As the item to be scanned moves along the conveyor, each thin volume orslice of it can be scanned once using the first set of detectors 512 aand then scanned again using the second set 512 b. In the embodimentshown, the same source 510 is used to scan two adjacent volumessimultaneously, with data for each of them being collected by arespective one of the detector sets 512 a, 512 b. After a volume of theitem has moved past both sets of detectors and scanned twice, two setsof image data can be formed using the two different X-ray energy ranges,each image including transmission (and hence attenuation) data for eachpixel of the image. The two sets of image data can be combined bysubtracting that for the second detector set 512 a from that of thefirst 512 b, resulting in corresponding image data for the low energyX-ray component.

The X-ray transmission data for each individual energy range, and thedifference between the data for two different ranges, such as the highenergy and low energy, can be recorded for each pixel of the image. Thedata can then be used to improve the accuracy of the CT images. It canalso be used as a further parameter in the threat detection algorithm.

It will be appreciated that other methods can be used to obtaintransmission data for different ranges of X-ray energies. In amodification to the system of FIGS. 18 and 19, balanced filters can beused on the two detector sets. The filters are selected such that thereis a narrow window of energies that is passed by both of them. The imagedata for the two sets of detectors can then be combined to obtaintransmission data for the narrow energy window. This enables chemicalspecific imaging to be obtained. For example it is possible to createbone specific images by using filters balanced around the calcium K-edgeenergy. Clearly this chemical specific data can be used effectively in athreat detection algorithm.

In a further embodiment, rather than using separate filters, two sets ofdetectors are used that are sensitive to different energy X-rays. Inthis case stacked detectors are used, comprising a thin front detectorthat is sensitive to low energy X-rays but allows higher energy X-raysto pass through it, and a thick back detector sensitive to the highenergy X-rays that pass through the front detector. Again theattenuation data for the different energy ranges can be used to provideenergy specific image data.

In a further embodiment two scans are taken of each slice of the objectwith two different X-ray beam energies, achieved by using different tubevoltages in the X-ray source, for example 160 kV and 100 kV. Thedifferent energies result in X-ray energy spectra that are shiftedrelative to each other. As the spectra are relatively flat over part ofthe energy range, the spectra will be similar over much of the range.However, part of the spectrum will change significantly. Thereforecomparing images for the two tube voltages can be used to identify partsof the object where the attenuation changes significantly between thetwo images. This therefore identifies areas of the image that have highattenuation in the narrow part of the spectrum that changes between theimages. This is therefore an alternative way of obtaining energyspecific attenuation data for each of the sub-volumes within the scannedvolume.

Referring to FIG. 20 in a further embodiment of the invention, twodifferent X-ray energy spectra are produced by providing an anode 600 inthe X-ray tube that has target areas 602, 604 of two differentmaterials. In this case, for example, the anode comprises a copper base606 with one target area 602 of tungsten and one 604 of uranium. Theelectron source 610 has a number of source points 612 that can beactivated individually. A pair of electrodes 612, 614 is provided onopposite sides of the path of the electron beam 616 which can becontrolled to switch an electric field on and off to control the path ofthe electron beam so that it strikes either one or the other of thetarget areas 602, 604. The energy spectrum of the X-rays produced at theanode will vary depending on which of the target areas is struck by theelectron beam 616.

This embodiment uses an X-ray source similar to that of FIG. la, withthe different target areas formed as parallel strips extending along theanode 27. For each active electron source point two different X-rayspectra can be produced depending on which target material is used. Thesource can be arranged to switch between the two target areas for eachelectron source point while it is active. Alternatively the scan alongthe anode 27 can be performed twice, once for one target material andonce for the other. In either case further electron beam focusing wiresmay be needed to ensure that only one or the other of the targetmaterials is irradiated by the electron beam at one time.

Depending on the angle at which the X-ray beam is extracted from theanode, the beams from the two target areas 602, 604 can in some cases bearranged to pass though the same imaging volume and be detected by acommon detector array. Alternatively they may be arranged to passthrough adjacent slices of the imaging volume and detected by separatedetector arrays. In this case the parts of the imaged item can bescanned twice as the item passes along the conveyor in a similar mannerto the arrangement of FIG. 18.

Referring to FIG. 21, in a further embodiment, two detector arrays areprovided in a single scanner, adjacent to each other in the axialdirection, one 710 corresponding to that of FIG. 1 and being arranged toform a RTT image, and the other, 712, being of a higher resolution, andbeing arranged to produce a high resolution projection image of thescanned object. In this embodiment the high resolution detector array712 comprises two parallel linear arrays 714, 716 each arranged todetect X-rays at a different energy, so that a dual energy projectionimage can be produced. In the embodiment of FIG. 22, the high resolutionarray 812 comprises two stacked arrays, a thin array on top arranged todetect lower energy X-rays but transparent to higher energy X-rays, anda thicker array beneath arranged to detect higher energy X-rays. In bothcases, the two detector arrays are arranged close enough together in theaxial direction to be able to detect X-rays from a single linear arrayof source points.

In order to provide a projection image, data needs to be captured fromall of the detectors in the high resolution array 712, 812 when only onesource point is active. Referring to FIG. 23, in order to do this eachdetector 718, 818 in the high resolution array is connected to anintegrator 750. The integrator comprises an amplifier 752 in parallelwith a capacitor 754. An input switch 756 is provided between thedetector 718 and the amplifier 752, a reset switch 758 is providedacross the input terminals of the amplifier, and a further reset switch759 connected across the capacitor 754, and a multiplexing switch 760 isprovided between the integrator and an analogue to digital converterADC.

In operation, while the detector 718 is not required to be active, allof the switches except for the multiplexing switch 760 are closed. Thisensures that the capacitor 754 is uncharged and remains so. Then, at thestart of the period when the detector is required to gather data, thetwo reset switches 758, 759 are closed so that any X-rays detected bythe detector 718 will cause an increase in the charge on the capacitor754, which results in integration of the signal from the detector 718.When the period for data collection has ended, the input switch 756 isopened, so that the capacitor will remain charged. Then, in order forthe integrated signal to be read from the integrator, the output switch760 is closed to connect the integrator to the ADC. This provides ananalogue signal to the ADC determined by the level of charge on thecapacitor 754, and therefore indicative of the number of X-rays thathave been detected by the detector 718 during the period for which itwas connected to the integrator. The ADC then converts this analoguesignal to a digital signal for input to the data acquisition system. Toproduce a single projection image, all of the high resolution detectorsare used to collect data at the same time, when one of the X-ray sourcepoints is active.

Referring to FIG. 24, in a further embodiment, each detector 718 isconnected to two integrators 750 a, 750 b in parallel, each of which isidentical to that of FIG. 23. The outputs from the two integrators areconnected via their output switches 760 a, 760 b to an ADC. This enableseach integrator to be arranged to integrate the signal from the detector718 at a different point in the scan of the X-ray source, and thereforeto collect data for a separate image, the two images being fromdifferent angles with different X-ray source points. For example thiscan be used to produce projection images from orthogonal directionswhich can be used to build up a high resolution 3-dimensional image,from which the position of features in the imaged package can bedetermined in three dimensions.

The high resolution image can be useful when combined with the RTTimage, as it can help identify items for which higher resolution isneeded, such as fine wires.

Liquids Detection

In a particular embodiment of the invention, the threat detectionprocessor, which executes programmatic instructions that process inputimage data 62 and code the decision trees 64 and parameter extractions63 shown in FIG. 5, is tuned for the detection of liquids. In anembodiment, a three-dimensional segmentation calculation is used forperforming liquid detection. Variations of segmentation calculations,commonly known to persons of ordinary skill in the art and based arounda surface detector (for example using a dilate-erode algorithm in allthree dimensions) and a volume filling algorithm that grows out from thedetected surface, can be implemented. In another embodiment, a volumefilling algorithm from a seed point which extends out until a surface isreached is used. In an exemplary embodiment, the surface is determinedby analyzing each new pixel in terms of its probability of being part ofthe volume or otherwise. A pixel value within, for example, one sigma ofthe mean value of the volume may be considered to be part of the volumewhile a pixel lying more than two sigma from the mean value may beconsidered to be not part of the volume. Seed points may be determinedby analyzing the image to find regions of similar pixel density andplacing a seed point at the centroid location of each such region. Invarious embodiments, a suitable method is determined based on thestatistical properties of the image, the type and severity of imagereconstruction artefacts in the image and the intrinsic spatialresolution of the image.

Referring to FIG. 5, a first parameter extraction block 63 is configuredto process the input image data 62 to identify a) an object underinspection, b) the outer envelope defining the object under inspection,and c) any flat surfaces within the outer envelope of the object underinspection which lie parallel to the surface of the conveyor in thehorizontal plane. Such parallel surfaces can be reliably used touniquely identify the existence of a liquid contained within a vessel.Next, a second parameter extraction block is configured to locate acontiguous volume of material of uniform density that extends from eachsuch parallel surface element in a vertical direction downwards towardsthe surface of the conveyor. This method uses a simplified version ofthe segmentation methods outlined above since the only direction ofimportance here is in the vertical plane rather than vertical andhorizontal planes.

The information obtained by the parameter extraction blocks is passedfrom the parameter extraction blocks 63 to an associated decision tree64, where the actual volume of the contiguous volume is calculated andassigned a fit to a predetermined shape matching one or more of ovalbottle, rectangular bottle and triangular bottle. The mean reconstructedintensity of the contiguous volume is calculated and this information(volume, shape, density) is passed to the database searcher 65.

Here, the information is compared against a database of known benignmaterials and known threat materials. For example, a 1.5 liter bottle ofsugar laden beverage will have a common exterior dimension ofapproximately 400 mm (L)×100 mm (diameter) within a thin plasticcontainer with a neck drawing in to a cap and a base with rounded ormoulded features. The density of such beverages is typically justgreater that that of water and the volume of the liquid will be nogreater than 1.5 liters within a container of volume just greater than1.5 liters. In contrast, an alcoholic beverage is more often in a glassbottle with thicker wall thickness with smaller volume such as 750 ml(bottle of wine) or 330 ml (spirit). Alcohol based bottles willgenerally be full (i.e. volume of liquid is close to volume ofcontainer) and will include characteristic features such as a cork orscrew top. Density of the liquid will also be in well known bands. Knownthreat materials tend to have density just below that of water and sostand out quite clearly. In the case that a clear match is made againsta benign material, then no further action is taken. In the case that athreat material is detected, an alarm shall be raised on the operatorworkstation and the threat object highlighted for further inspection. Inone embodiment, density calculations are obtained and then compared, bythe processor, against liquid densities stored in a database.

Using a high resolution three dimensional image, such as is obtainedusing the system of the present invention, allows a very accurateestimate of liquid volume to be made which helps substantially inseparating a full vessel from a partially filled bottle. It is notedthat virtually all liquids are sold in standard sized quantities (e.g.1500 ml, 1000 ml, 750 ml, 500 ml, 330 ml, 250 ml) with a high level offilling accuracy. Thus, volume estimation can play a key role indetecting vessels which have been tampered with. The high speed oftransit of the object through the data acquisition system of the presentinvention causes the liquid to have “waves” on its surface. The highspeed of data acquisition enables reconstruction of the shape of thesewaves which are themselves characteristic of the viscosity of the fluidwithin the container. This additional information is then used to enabledifferentiation in detection of one liquid from another.

It shall be evident to one skilled in the art that the architecturedescribed here is capable of being implemented in a parallelarchitecture and that therefore multiple algorithms can be constructed,each looking for either the same type of feature or quite differenttypes of feature (such as liquids and narcotics) at the same time.

Narcotics

In a particular embodiment of the invention, the threat detectionprocessor, which executes programmatic instructions that process inputimage data 62 and code the decision trees 64 and parameter extractions63 shown in FIG. 5, is tuned for the detection of narcotics.

In an embodiment, the threat detection processor is tuned by selectingalgorithms used in the parameter extraction blocks and by weighting ofthe results from the parameter extraction blocks 63 as they propagatethrough the decision trees 64. In an embodiment, the tuning informationis stored in the form of parameters which can be updated easily withouthaving to re-program the underlying algorithms and methods.

For detection of narcotics, a first parameter block 63 is tuned toprocess the input image data 62 to look for contiguous volumes of lowdensity material in both sheet and bulk shapes. In an exemplaryembodiment, volumes in the range 1 g/cm3 to 3 g/cm3 are identified. Asecond parameter block processes these same volumes to determine basicstatistical properties of the contiguous volumes to include mean value,standard deviation and skew. A third parameter block searches forcollections of randomly oriented parts of small volume which may bedetermined to be pharmaceuticals. Such randomly oriented particlesinclude tablets in a jar or bag while a structured arrangement oftablets may be observed in pop-out packaging materials. All of this data(volume, shape and statistical properties) is passed to the decisiontree which correlates the data from the multiple parameter blocks.

The data is then passed to the database searcher 65 where the data iscompared against values stored in a database of known threat materials.It is recognised that raw narcotics, such a heroin or cocaine in powderform, tend to be packaged in relatively ordered shapes with very thin,generally polythene, wrapping. Thus, a package of volume 5 cm3 upwardsto 100 cm3 with almost undetectable wrapping with density in the range 1g/cm3 to 3 g/cm3 is likely to be a suspect bulk narcotic material. Wherea close match is determined, an alarm shall be raised on the operatorworkstation and the threat items highlighted for further inspection.

Currency

In a particular embodiment of the invention, the threat detectionprocessor, which executes programmatic instructions that process inputimage data 62 and code the decision trees 64 and parameter extractions63 shown in FIG. 5, is tuned for the detection of currency . It shall beevident to a person skilled in the art that a parallel algorithmarchitecture may be implemented which allows simultaneous detection ofcurrency and other potential threat items.

Here a first parameter block 63 is tuned to look for “bow-tie” shapedfeatures in the object under inspection. Bundles of currency aretypically bound towards their centre, such that the centre of a bundleis marginally thinner than the ends. A second parameter block is tunedto search for rectangular shapes in multiples of the physical dimensionof common denominations of currency. A third parameter block is tuned tolook for repeating patterns in the blocks found by the first twoparameter blocks. These patterns are characteristic of the stacks ofindividual bundles that tend to be used to make up a collection ofcurrency. A fourth parameter block is tuned to generate statisticalproperties of the bundles identified by the other three parameterblocks. As an example, a stack of US dollar bills will have a welldefined area (approx 150 mm×65 mm) with a thickness which is dependenton the amount of currency involved. The thicker the stack, the less thebow-tie effect. However, each type of currency has certain securityfeatures embedded into it (such as a metal strip) or a variation inmaterial type or printing density. This arrangement of subtleinformation is amplified when many notes are stacked together and can beregistered by a repeating block algorithm. This collection ofinformation is passed to the decision tree 64 which correlates theinformation from the currency specific parameter blocks with the datafrom all the other parameter blocks and the complete setoff data ispassed to the database searcher 65. When a clear match is found betweenan item in the cargo under inspection and a know type of currency, analarm is raised on the operator workstation and the relevant currency ishighlighted for further inspection.

Tobacco

In a particular embodiment of the invention, the threat detectionprocessor, which executes programmatic instructions that process inputimage data 62 and code the decision trees 64 and parameter extractions63 shown in FIG. 5, is tuned for the detection of tobacco, andcigarettes in particular. Cigarettes are characterized by a veryrepeatable structure which is first determined by the length anddiameter of individual cigarettes. Secondly, groups of 10 and/or 20cigarettes are packed together into a box of known and repeatable size.Thirdly, groups of boxes of cigarettes are packed into arrays of dozensof boxes which occupy a significant volume. Therefore, a first parameterblock 63 is tuned to look for repeating array structures with a lengthand width dimension consistent with known dimensions of cigarettes. Asecond parameter block is tuned to detect rectangular volumes ofpredefined aspect ratio matching that of common cigarette packaging witha density that is consistent with typical brands of cigarettes. Theresults from these two parameter blocks are passed through to a decisiontree which correlates the data with other known data from the objectunder inspection.

If, an exemplary brand of cigarette has an overall length of 90 mm witha filter length of 15 mm and a diameter of 8 mm, a pack of 20 cigaretteswill therefore have an external dimension of 92 mm (L)×82 mm (W)×22 m(D). This constitutes, at least in part, the regular repeating structurewhich is stacked into a larger overall volume. A stack of 48 packetsarranged in a 6×8 configuration will have an overall dimension of 132 mm(H)×656 mm (W)×92 mm (D). Within thus structure will be a set ofrectangular planes which are established by the higher density cardboardboxes and it is all of this information which is picked up by theautomated detection algorithm

This information is then passed to a database search which compares theinformation with known tobacco products. When a clear match is foundbetween an item in the cargo under inspection and a known type oftobacco, and alarm is raised on the operator workstation and therelevant tobacco product is highlighted for inspection. As would beapparent to a person skilled in the art, similar algorithms may beimplemented for the detection of cigars and related products.

Nuclear Materials

In a particular embodiment of the invention, the threat detectionprocessor, which executes programmatic instructions that process inputimage data 62 and code the decision trees 64 and parameter extractions63 shown in FIG. 5, is tuned for the detection of special nuclearmaterials, such as Uranium and Plutonium, and for other shieldedradioactive sources such as cobalt-60 and cesium-137. In this case, afirst parameter extractor 63 is tuned to look for highly attenuatingregions in the image where the reconstructed pixel intensity is above athreshold value. This data is passed to the decision tree which seeks todetermine whether the attenuating object is part of a larger structure(such as metallic rails which are commonly used to support the frameworkof a piece of baggage). If the object(s) located by the parameterextractor can not be linked to other structures, the decision tree willevaluate shape, location (for example, is the attenuation object at thesurface of the cargo item in which case it may be a fastener) and sizeprior to passing the new data on to the database search tool. If a matchis found between the dark object and a set of characteristics that arecommon to radioactive sources (typically no re-entrant volume of lowerintensity), then an alarm is raised on the operator workstation and therelevant nuclear material is highlighted for inspection. As is commonlyknown in the art, high density shielding typically has a density of 11g/cm3 (lead) and above. Standard engineering materials (e.g. steel) tendto have a density of 8 g/cm3 and below. This specific range enables thedetection of radioactive source shielding relatively easily.

Points and Knives

In a particular embodiment of the invention, the threat detectionprocessor, which executes programmatic instructions that process inputimage data 62 and code the decision trees 64 and parameter extractions63 shown in FIG. 5, is tuned for the detection of sharp objects andknives. Sharp objects are characterized by the presence of a sharp pointwhich is typically distinguished from points that might occur at thenon-threatening corners of rectangular objects such as books andelectrical goods. Knives are further characterised by the presence of ablade shape which is typically long in one dimension compared toanother. In many cases, blades are folded into a supporting housing,and, in this case, the blade is characterized by a repeating structureof high density (case or blade) and low density (surrounding air). Afirst parameter extractor is tuned for the detection of protrudingpoints and not simply corners. A second parameter extractor is tuned forthe detection of blades in which there is a significant length to widthaspect ratio. A third parameter extractor is tuned for the detection offolded blades in which there is a repeating structure of at least twoair gaps and three material fills.

For example, a three inch blade generally has an aspect ratio(length:width) of at least 3:1 while a six inch blade that of at least6:1. The width of a blade is generally in proportion to its length, witha width to length ratio on the order of 1:60, and typically less than1:100 but more than 1:20. Data from these parameter extractors is passedto a decision tree which correlates the data with associated informationsuch as the presence of a handle on a knife.

The filtered information is then passed to a database searcher whichanalyses the data against known threat items. If a reasonable match isdetermined, an alarm is raised on the operator workstation and therelevant point or blade is highlighted for further inspection.

Fire-Arms

In a particular embodiment of the invention, the threat detectionprocessor, which executes programmatic instructions that process inputimage data 62 and code the decision trees 64 and parameter extractions63 shown in FIG. 5, is tuned for the detection of fire-arms, includinggun barrels, steel tubes of a certain diameter (or range of diameters),rifles; and ammunition (a high density slug such as lead, copper,tungsten) next to and connected to a brass cylinder loaded with powderof a known range of densities.

Fire-arms are characterized by the presence of metallic tubes of acertain diameter. Accordingly, a first parameter extractor is tuned forthe detection of cylindrical metal tubes. A second parameter extractoris tuned for detection of a trigger mechanism and firing pin. A thirdparameter extractor is tuned for detection of high density slugs andbullets with composition ranging from aluminium (density 2.7 g/cm3) tolead (density>11 g/cm3). Generally, bullets will have a lower densitycore filled with gun powder (density typically 1 g/cm3).

Data from these parameter extractors is passed to a decision tree whichcorrelates the data with associated information such as the presence ofa gun barrel. The filtered information is then passed to a databasesearcher which analyses the data against known threat items. If areasonable match is determined, an alarm is raised on the operatorworkstation and the relevant cylinder is highlighted for furtherinspection.

We claim:
 1. An X-ray scanning system comprising: a. a non-rotatingX-ray scanner that generates scanning data defining a tomographic X-rayimage of the object; and b. a processor executing programmaticinstructions wherein said executing processor analyzes the scanning datato extract at least one parameter of the tomographic X-ray image andwherein said processor is configured to determine if said object is abottle containing a liquid.
 2. The X-ray scanning system of claim 1wherein said processor executes programmatic instructions to allocatethe object to one of a plurality of categories on the basis of the atleast one parameter.
 3. The X-ray scanning system of claim 2 whereinsaid programmatic instructions comprise at least one parameter extractorfor identifying at least one predefined feature in the tomographic X-rayimage wherein said predefined feature comprises a plurality of low levelparameters of the X-ray image.
 4. The X-ray scanning system of claim 3wherein said programmatic instructions comprise at least one decisiontree for constructing high level parameters based upon the identifiedlow level parameters of the X-ray image.
 5. The X-ray system of claim 4wherein said high level parameters include a contiguous volume, apredetermined shape, or a mean reconstructed density of the contiguousvolume.
 6. The X-ray scanning system of claim 4 further comprising adatabase search tool for mapping the constructed high level parametersof the X-ray image to predefined data stored in a database.
 7. The X-rayscanning system of claim 6 further comprising an alarm system foractivating an alarm based on a result of said mapping, wherein saidalarm defines an object as being a potential threat or not a potentialthreat.
 8. The X-ray scanning system as claimed in claim 3 wherein theat least one parameter extractor is configured to operate on one2-dimensional images, 3-dimensional images or sinogram image data.
 9. AnX-ray scanning system comprising: a. a non-rotating X-ray scanner thatgenerates scanning data defining a tomographic X-ray image of theobject; and b. a processor executing programmatic instructions whereinsaid executing processor analyzes the scanning data to extract at leastone parameter of the tomographic X-ray image and wherein said processoris configured to determine if said object comprises a sharp object. 10.The X-ray scanning system of claim 9 wherein said processor executesprogrammatic instructions to allocate the object to one of a pluralityof categories on the basis of the at least one parameter.
 11. The X-rayscanning system of claim 10 wherein said programmatic instructionscomprise at least one parameter extractor for identifying at least onepredefined feature in the tomographic X-ray image wherein saidpredefined feature comprises a plurality of low level parameters of theX-ray image.
 12. The X-ray scanning system of claim 11 wherein saidprogrammatic instructions comprise at least one decision tree forconstructing high level parameters based upon the identified low levelparameters of the X-ray image.
 13. The X-ray system of claim 12 whereinsaid high level parameters include a structure having a predefinedlength to width aspect ratio or a predefined repeating structure. 14.The X-ray scanning system of claim 12 further comprising a databasesearch tool for mapping the constructed high level parameters of theX-ray image to predefined data stored in a database.
 15. The X-rayscanning system of claim 14 further comprising an alarm system foractivating an alarm based on a result of said mapping, wherein saidalarm defines an object as being a potential threat or not a potentialthreat.
 16. The X-ray scanning system as claimed in claim 11 wherein theat least one parameter extractor is configured to operate on one2-dimensional images, 3-dimensional images or sinogram image data. 17.An X-ray scanning system comprising: a. a non-rotating X-ray scannerthat generates scanning data defining a tomographic X-ray image of theobject; and b. a processor executing programmatic instructions whereinsaid executing processor analyzes the scanning data to extract at leastone parameter of the tomographic X-ray image and wherein said processoris configured to determine if said object comprises a narcotic,currency, nuclear materials, cigarettes or fire-arms.
 18. The X-rayscanning system of claim 17 wherein said processor executes programmaticinstructions to allocate the object to one of a plurality of categorieson the basis of the at least one parameter.
 19. The X-ray scanningsystem of claim 17 wherein said programmatic instructions comprise atleast one parameter extractor for identifying at least one predefinedfeature in the tomographic X-ray image wherein said predefined featurecomprises a plurality of low level parameters of the X-ray image. 20.The X-ray scanning system of claim 19 wherein said programmaticinstructions comprise at least one decision tree for constructing highlevel parameters based upon the identified low level parameters of theX-ray image.
 21. The X-ray system of claim 20 wherein said high levelparameters include structures having a predefined length to width aspectratio or a predefined repeating structure.
 22. The X-ray scanning systemof claim 20 further comprising a database search tool for mapping theconstructed high level parameters of the X-ray image to predefined datastored in a database.
 23. The X-ray scanning system of claim 22 furthercomprising an alarm system for activating an alarm based on a result ofsaid mapping, wherein said alarm defines an object as being a potentialthreat or not a potential threat.
 24. The X-ray scanning system asclaimed in claim 19 wherein the at least one parameter extractor isconfigured to operate on one 2-dimensional images, 3-dimensional imagesor sinogram image data.